Code profiling for Shiny app?

Question

For an R Shiny web app, what are some good ways to run code profiling that show the parts of the Shiny code that are taking the most processing time?

I\'ve got a bi

Answer 1

I think this question needs a little update, therefore I am adding another answer to it...

You can use the package profvis to profile shiny apps as well. It will give flame graphs directly for your R code. I.e. no need to use Chrome's flame graphs and guess where the bottleneck is. You will know exactly where to change your code.

Here is how to do it:

1. Run shiny app via Profvis
2. Interact with your shiny app
3. Close browser
4. Stop Console via Stop button
5. Load profile
6. If Step 5 fails, try this: Convert to html if needed (memory problems)

Details for certain steps are added below:

Step 1: Run profvis

library(profvis)
profvis({ runApp('directory_of_shiny_app') }  
    , prof_output = '/directory_to_save_profile')

Step 5: Load your profile

profvis(prof_input = '/path_to_save_output/random_name.Rprof') 

N.B. Profvis gives a random name to your file. So you need to change the input path accordingly

Step 6: Convert to html

This step might be needed, if you have a huge app and flame graph gets a little bit longer. You might get an error "Pandoc:... memory"

p <- profvis(prof_input = '/path_to_save_output/file108f93bff877b.Rprof')
htmlwidgets::saveWidget(p, "/path_to_save_output/profile.html")

Then open the html file in your browser.